/[escript]/trunk/escript/py_src/util.py
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revision 117 by jgs, Fri Apr 1 05:48:57 2005 UTC revision 126 by jgs, Fri Jul 22 03:53:08 2005 UTC
# Line 4  Line 4 
4    
5  """  """
6  @brief Utility functions for escript  @brief Utility functions for escript
7    
8    TODO for Data:
9    
10      * binary operations @:               (a@b)[:,*]=a[:]@b[:,*] if rank(a)<rank(b)
11                    @=+,-,*,/,**           (a@b)[:]=a[:]@b[:] if rank(a)=rank(b)
12                                           (a@b)[*,:]=a[*,:]@b[:] if rank(a)>rank(b)
13      
14      * implementation of outer outer(a,b)[:,*]=a[:]*b[*]
15      * trace: trace(arg,axis0=a0,axis1=a1)(:,&,*)=sum_i trace(:,i,&,i,*) (i are at index a0 and a1)
16  """  """
17    
18  import numarray  import numarray
19  import escript  import escript
20    
21  #  #
22  #   escript constants (have to be consistent witj utilC.h  #   escript constants (have to be consistent with utilC.h )
23  #  #
24  UNKNOWN=-1  UNKNOWN=-1
25  EPSILON=1.e-15  EPSILON=1.e-15
# Line 50  OPENINVENTOR=8 Line 60  OPENINVENTOR=8
60  RENDERMAN=9  RENDERMAN=9
61  PNM=10  PNM=10
62    
63  #  #===========================================================
64  # wrapper for various functions: if the argument has attribute the function name  # a simple tool box to deal with _differentials of functions
65  # as an argument it calls the correspong methods. Otherwise the coresponsing numarray  #===========================================================
66  # function is called.  
67  #  class Symbol:
68  # functions involving the underlying Domain:     """symbol class"""
69  #     def __init__(self,name="symbol",shape=(),dim=3,args=[]):
70  def grad(arg,where=None):         """creates an instance of a symbol of shape shape and spatial dimension dim
71      """            The symbol may depending on a list of arguments args which
72      @brief returns the spatial gradient of the Data object arg            may be symbols or other objects. name gives the name of the symbol."""
73           self.__args=args
74           self.__name=name
75           self.__shape=shape
76           if hasattr(dim,"getDim"):
77               self.__dim=dim.getDim()
78           else:    
79               self.__dim=dim
80           #
81           self.__cache_val=None
82           self.__cache_argval=None
83    
84       def getArgument(self,i):
85           """returns the i-th argument"""
86           return self.__args[i]
87    
88       def getDim(self):
89           """returns the spatial dimension of the symbol"""
90           return self.__dim
91    
92       def getRank(self):
93           """returns the rank of the symbol"""
94           return len(self.getShape())
95    
96       def getShape(self):
97           """returns the shape of the symbol"""
98           return self.__shape
99    
100       def getEvaluatedArguments(self,argval):
101           """returns the list of evaluated arguments by subsituting symbol u by argval[u]."""
102           if argval==self.__cache_argval:
103               print "%s: cached value used"%self
104               return self.__cache_val
105           else:
106               out=[]
107               for a  in self.__args:
108                  if isinstance(a,Symbol):
109                    out.append(a.eval(argval))
110                  else:
111                    out.append(a)
112               self.__cache_argval=argval
113               self.__cache_val=out
114               return out
115    
116       def getDifferentiatedArguments(self,arg):
117           """returns the list of the arguments _differentiated by arg"""
118           out=[]
119           for a in self.__args:
120              if isinstance(a,Symbol):
121                out.append(a.diff(arg))
122              else:
123                out.append(0)
124           return out
125    
126      @param arg: Data object representing the function which gradient to be calculated.     def diff(self,arg):
127      @param where: FunctionSpace in which the gradient will be. If None Function(dom) where dom is the         """returns the _differention of self by arg."""
128                    domain of the Data object arg.         if self==arg:
129      """            out=numarray.zeros(tuple(2*list(self.getShape())),numarray.Float)
130      if isinstance(arg,escript.Data):            if self.getRank()==0:
131         if where==None:               out=1.
132            return arg.grad()            elif self.getRank()==1:
133                  for i0 in range(self.getShape()[0]):
134                     out[i0,i0]=1.  
135              elif self.getRank()==2:
136                  for i0 in range(self.getShape()[0]):
137                    for i1 in range(self.getShape()[1]):
138                         out[i0,i1,i0,i1]=1.  
139              elif self.getRank()==3:
140                  for i0 in range(self.getShape()[0]):
141                    for i1 in range(self.getShape()[1]):
142                      for i2 in range(self.getShape()[2]):
143                         out[i0,i1,i2,i0,i1,i2]=1.  
144              elif self.getRank()==4:
145                  for i0 in range(self.getShape()[0]):
146                    for i1 in range(self.getShape()[1]):
147                      for i2 in range(self.getShape()[2]):
148                        for i3 in range(self.getShape()[3]):
149                           out[i0,i1,i2,i3,i0,i1,i2,i3]=1.  
150              else:
151                 raise ValueError,"differential support rank<5 only."
152              return out
153         else:         else:
154            return arg.grad(where)            return self._diff(arg)
     else:  
        return arg*0.  
   
 def integrate(arg,what=None):  
     """  
     @brief return the integral if the function represented by Data object arg over its domain.  
   
     @param arg  
     """  
     if not what==None:  
        arg2=escript.Data(arg,what)  
     else:  
        arg2=arg  
     if arg2.getRank()==0:  
         return arg2.integrate()[0]  
     else:  
         return arg2.integrate()  
155    
156  def interpolate(arg,where):     def _diff(self,arg):
157      """         """return derivate of self with respect to arg (!=self).
158      @brief interpolates the function represented by Data object arg into the FunctionSpace where.            This method is overwritten by a particular symbol"""
159           return 0
160    
161       def eval(self,argval):
162           """subsitutes symbol u in self by argval[u] and returns the result. If
163              self is not a key of argval then self is returned."""
164           if argval.has_key(self):
165             return argval[self]
166           else:
167             return self
168    
169      @param arg     def __str__(self):
170      @param where         """returns a string representation of the symbol"""
171      """         return self.__name
172      if isinstance(arg,escript.Data):  
173         return arg.interpolate(where)     def __add__(self,other):
174      else:         """adds other to symbol self. if _testForZero(other) self is returned."""
175         return arg         if _testForZero(other):
176              return self
177           else:
178              a=_matchShape([self,other])
179              return Add_Symbol(a[0],a[1])
180    
181  # functions returning Data objects:     def __radd__(self,other):
182           """adds other to symbol self. if _testForZero(other) self is returned."""
183           return self+other
184    
185       def __neg__(self):
186           """returns -self."""
187           return self*(-1.)
188    
189       def __pos__(self):
190           """returns +self."""
191           return self
192    
193       def __abs__(self):
194           """returns absolute value"""
195           return Abs_Symbol(self)
196    
197       def __sub__(self,other):
198           """subtracts other from symbol self. if _testForZero(other) self is returned."""
199           if _testForZero(other):
200              return self
201           else:
202              return self+(-other)
203    
204  def transpose(arg,axis=None):     def __rsub__(self,other):
205      """         """subtracts symbol self from other."""
206      @brief returns the transpose of the Data object arg.         return -self+other
207    
208       def __div__(self,other):
209           """divides symbol self by other."""
210           if isinstance(other,Symbol):
211              a=_matchShape([self,other])
212              return Div_Symbol(a[0],a[1])
213           else:
214              return self*(1./other)
215    
216      @param arg     def __rdiv__(self,other):
217      """         """dived other by symbol self. if _testForZero(other) 0 is returned."""
218      if isinstance(arg,escript.Data):         if _testForZero(other):
219         # hack for transpose            return 0
220         r=arg.getRank()         else:
221         if r!=2: raise ValueError,"Tranpose only avalaible for rank 2 objects"            a=_matchShape([self,other])
222         s=arg.getShape()            return Div_Symbol(a[0],a[1])
        out=escript.Data(0.,(s[1],s[0]),arg.getFunctionSpace())  
        for i in range(s[0]):  
           for j in range(s[1]):  
              out[j,i]=arg[i,j]  
        return out  
        # end hack for transpose  
        if axis==None: axis=arg.getRank()/2  
        return arg.transpose(axis)  
     else:  
        if axis==None: axis=arg.rank/2  
        return numarray.transpose(arg,axis=axis)  
223    
224  def trace(arg):     def __pow__(self,other):
225      """         """raises symbol self to the power of other"""
226      @brief         a=_matchShape([self,other])
227           return Power_Symbol(a[0],a[1])
228    
229       def __rpow__(self,other):
230           """raises other to the symbol self"""
231           a=_matchShape([self,other])
232           return Power_Symbol(a[1],a[0])
233    
234       def __mul__(self,other):
235           """multiplies other by symbol self. if _testForZero(other) 0 is returned."""
236           if _testForZero(other):
237              return 0
238           else:
239              a=_matchShape([self,other])
240              return Mult_Symbol(a[0],a[1])
241    
242      @param arg     def __rmul__(self,other):
243      """         """multiplies other by symbol self. if _testSForZero(other) 0 is returned."""
244      if isinstance(arg,escript.Data):         return self*other
245         # hack for trace  
246         r=arg.getRank()     def __getitem__(self,sl):
247         if r!=2: raise ValueError,"trace only avalaible for rank 2 objects"            print sl
248         s=arg.getShape()  
249         out=escript.Scalar(0,arg.getFunctionSpace())  def Float_Symbol(Symbol):
250         for i in range(min(s)):      def __init__(self,name="symbol",shape=(),args=[]):
251               out+=arg[i,i]          Symbol.__init__(self,dim=0,name="symbol",shape=(),args=[])
252         return out  
253         # end hack for trace  class ScalarSymbol(Symbol):
254         return arg.trace()     """a scalar symbol"""
255      else:     def __init__(self,dim=3,name="scalar"):
256         return numarray.trace(arg)        """creates a scalar symbol of spatial dimension dim"""
257          if hasattr(dim,"getDim"):
258               d=dim.getDim()
259          else:    
260               d=dim
261          Symbol.__init__(self,shape=(),dim=d,name=name)
262    
263    class VectorSymbol(Symbol):
264       """a vector symbol"""
265       def __init__(self,dim=3,name="vector"):
266          """creates a vector symbol of spatial dimension dim"""
267          if hasattr(dim,"getDim"):
268               d=dim.getDim()
269          else:    
270               d=dim
271          Symbol.__init__(self,shape=(d,),dim=d,name=name)
272    
273    class TensorSymbol(Symbol):
274       """a tensor symbol"""
275       def __init__(self,dim=3,name="tensor"):
276          """creates a tensor symbol of spatial dimension dim"""
277          if hasattr(dim,"getDim"):
278               d=dim.getDim()
279          else:    
280               d=dim
281          Symbol.__init__(self,shape=(d,d),dim=d,name=name)
282    
283    class Tensor3Symbol(Symbol):
284       """a tensor order 3 symbol"""
285       def __init__(self,dim=3,name="tensor3"):
286          """creates a tensor order 3 symbol of spatial dimension dim"""
287          if hasattr(dim,"getDim"):
288               d=dim.getDim()
289          else:    
290               d=dim
291          Symbol.__init__(self,shape=(d,d,d),dim=d,name=name)
292    
293    class Tensor4Symbol(Symbol):
294       """a tensor order 4 symbol"""
295       def __init__(self,dim=3,name="tensor4"):
296          """creates a tensor order 4 symbol of spatial dimension dim"""    
297          if hasattr(dim,"getDim"):
298               d=dim.getDim()
299          else:    
300               d=dim
301          Symbol.__init__(self,shape=(d,d,d,d),dim=d,name=name)
302    
303    class Add_Symbol(Symbol):
304       """symbol representing the sum of two arguments"""
305       def __init__(self,arg0,arg1):
306           a=[arg0,arg1]
307           Symbol.__init__(self,dim=_extractDim(a),shape=_extractShape(a),args=a)
308       def __str__(self):
309          return "(%s+%s)"%(str(self.getArgument(0)),str(self.getArgument(1)))
310       def eval(self,argval):
311           a=self.getEvaluatedArguments(argval)
312           return a[0]+a[1]
313       def _diff(self,arg):
314           a=self.getDifferentiatedArguments(arg)
315           return a[0]+a[1]
316    
317    class Mult_Symbol(Symbol):
318       """symbol representing the product of two arguments"""
319       def __init__(self,arg0,arg1):
320           a=[arg0,arg1]
321           Symbol.__init__(self,dim=_extractDim(a),shape=_extractShape(a),args=a)
322       def __str__(self):
323          return "(%s*%s)"%(str(self.getArgument(0)),str(self.getArgument(1)))
324       def eval(self,argval):
325           a=self.getEvaluatedArguments(argval)
326           return a[0]*a[1]
327       def _diff(self,arg):
328           a=self.getDifferentiatedArguments(arg)
329           return self.getArgument(1)*a[0]+self.getArgument(0)*a[1]
330    
331    class Div_Symbol(Symbol):
332       """symbol representing the quotient of two arguments"""
333       def __init__(self,arg0,arg1):
334           a=[arg0,arg1]
335           Symbol.__init__(self,dim=_extractDim(a),shape=_extractShape(a),args=a)
336       def __str__(self):
337          return "(%s/%s)"%(str(self.getArgument(0)),str(self.getArgument(1)))
338       def eval(self,argval):
339           a=self.getEvaluatedArguments(argval)
340           return a[0]/a[1]
341       def _diff(self,arg):
342           a=self.getDifferentiatedArguments(arg)
343           return (a[0]*self.getArgument(1)-self.getArgument(0)*a[1])/ \
344                              (self.getArgument(1)*self.getArgument(1))
345    
346    class Power_Symbol(Symbol):
347       """symbol representing the power of the first argument to the power of the second argument"""
348       def __init__(self,arg0,arg1):
349           a=[arg0,arg1]
350           Symbol.__init__(self,dim=_extractDim(a),shape=_extractShape(a),args=a)
351       def __str__(self):
352          return "(%s**%s)"%(str(self.getArgument(0)),str(self.getArgument(1)))
353       def eval(self,argval):
354           a=self.getEvaluatedArguments(argval)
355           return a[0]**a[1]
356       def _diff(self,arg):
357           a=self.getDifferentiatedArguments(arg)
358           return self*(a[1]*log(self.getArgument(0))+self.getArgument(1)/self.getArgument(0)*a[0])
359    
360    class Abs_Symbol(Symbol):
361       """symbol representing absolute value of its argument"""
362       def __init__(self,arg):
363           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
364       def __str__(self):
365          return "abs(%s)"%str(self.getArgument(0))
366       def eval(self,argval):
367           return abs(self.getEvaluatedArguments(argval)[0])
368       def _diff(self,arg):
369           return sign(self.getArgument(0))*self.getDifferentiatedArguments(arg)[0]
370    
371    #=========================================================
372    #   some little helpers
373    #=========================================================
374    def _testForZero(arg):
375       """returns True is arg is considered of being zero"""
376       if isinstance(arg,int):
377          return not arg>0
378       elif isinstance(arg,float):
379          return not arg>0.
380       elif isinstance(arg,numarray.NumArray):
381          a=abs(arg)
382          while isinstance(a,numarray.NumArray): a=numarray.sometrue(a)
383          return not a>0
384       else:
385          return False
386    
387    def _extractDim(args):
388        dim=None
389        for a in args:
390           if hasattr(a,"getDim"):
391              d=a.getDim()
392              if dim==None:
393                 dim=d
394              else:
395                 if dim!=d: raise ValueError,"inconsistent spatial dimension of arguments"
396        if dim==None:
397           raise ValueError,"cannot recover spatial dimension"
398        return dim
399    
400    def _identifyShape(arg):
401       """identifies the shape of arg."""
402       if hasattr(arg,"getShape"):
403           arg_shape=arg.getShape()
404       elif hasattr(arg,"shape"):
405         s=arg.shape
406         if callable(s):
407           arg_shape=s()
408         else:
409           arg_shape=s
410       else:
411           arg_shape=()
412       return arg_shape
413    
414    def _extractShape(args):
415        """extracts the common shape of the list of arguments args"""
416        shape=None
417        for a in args:
418           a_shape=_identifyShape(a)
419           if shape==None: shape=a_shape
420           if shape!=a_shape: raise ValueError,"inconsistent shape"
421        if shape==None:
422           raise ValueError,"cannot recover shape"
423        return shape
424    
425    def _matchShape(args,shape=None):
426        """returns the list of arguments args as object which have all the specified shape.
427           if shape is not given the shape "largest" shape of args is used."""
428        # identify the list of shapes:
429        arg_shapes=[]
430        for a in args: arg_shapes.append(_identifyShape(a))
431        # get the largest shape (currently the longest shape):
432        if shape==None: shape=max(arg_shapes)
433        
434        out=[]
435        for i in range(len(args)):
436           if shape==arg_shapes[i]:
437              out.append(args[i])
438           else:
439              if len(shape)==0: # then len(arg_shapes[i])>0
440                raise ValueError,"cannot adopt shape of %s to %s"%(str(args[i]),str(shape))
441              else:
442                if len(arg_shapes[i])==0:
443                    out.append(outer(args[i],numarray.ones(shape)))        
444                else:  
445                    raise ValueError,"cannot adopt shape of %s to %s"%(str(args[i]),str(shape))
446        return out  
447    
448    #=========================================================
449    #   wrappers for various mathematical functions:
450    #=========================================================
451    def diff(arg,dep):
452        """returns the derivative of arg with respect to dep. If arg is not Symbol object
453           0 is returned"""
454        if isinstance(arg,Symbol):
455           return arg.diff(dep)
456        elif hasattr(arg,"shape"):
457              if callable(arg.shape):
458                  return numarray.zeros(arg.shape(),numarray.Float)
459              else:
460                  return numarray.zeros(arg.shape,numarray.Float)
461        else:
462           return 0
463    
464  def exp(arg):  def exp(arg):
465      """      """
466      @brief      @brief applies the exponential function to arg
467        @param arg (input): argument
     @param arg  
468      """      """
469      if isinstance(arg,escript.Data):      if isinstance(arg,Symbol):
470           return Exp_Symbol(arg)
471        elif hasattr(arg,"exp"):
472         return arg.exp()         return arg.exp()
473      else:      else:
474         return numarray.exp(arg)         return numarray.exp(arg)
475    
476    class Exp_Symbol(Symbol):
477       """symbol representing the power of the first argument to the power of the second argument"""
478       def __init__(self,arg):
479           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
480       def __str__(self):
481          return "exp(%s)"%str(self.getArgument(0))
482       def eval(self,argval):
483           return exp(self.getEvaluatedArguments(argval)[0])
484       def _diff(self,arg):
485           return self*self.getDifferentiatedArguments(arg)[0]
486    
487  def sqrt(arg):  def sqrt(arg):
488      """      """
489      @brief      @brief applies the squre root function to arg
490        @param arg (input): argument
     @param arg  
491      """      """
492      if isinstance(arg,escript.Data):      if isinstance(arg,Symbol):
493           return Sqrt_Symbol(arg)
494        elif hasattr(arg,"sqrt"):
495         return arg.sqrt()         return arg.sqrt()
496      else:      else:
497         return numarray.sqrt(arg)         return numarray.sqrt(arg)      
498    
499    class Sqrt_Symbol(Symbol):
500       """symbol representing square root of argument"""
501       def __init__(self,arg):
502           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
503       def __str__(self):
504          return "sqrt(%s)"%str(self.getArgument(0))
505       def eval(self,argval):
506           return sqrt(self.getEvaluatedArguments(argval)[0])
507       def _diff(self,arg):
508           return (-0.5)/self*self.getDifferentiatedArguments(arg)[0]
509    
510    def log(arg):
511        """
512        @brief applies the logarithmic function bases exp(1.) to arg
513        @param arg (input): argument
514        """
515        if isinstance(arg,Symbol):
516           return Log_Symbol(arg)
517        elif hasattr(arg,"log"):
518           return arg.log()
519        else:
520           return numarray.log(arg)
521    
522    class Log_Symbol(Symbol):
523       """symbol representing logarithm of the argument"""
524       def __init__(self,arg):
525           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
526       def __str__(self):
527          return "log(%s)"%str(self.getArgument(0))
528       def eval(self,argval):
529           return log(self.getEvaluatedArguments(argval)[0])
530       def _diff(self,arg):
531           return self.getDifferentiatedArguments(arg)[0]/self.getArgument(0)
532    
533    def ln(arg):
534        """
535        @brief applies the natural logarithmic function to arg
536        @param arg (input): argument
537        """
538        if isinstance(arg,Symbol):
539           return Ln_Symbol(arg)
540        elif hasattr(arg,"ln"):
541           return arg.log()
542        else:
543           return numarray.log(arg)
544    
545    class Ln_Symbol(Symbol):
546       """symbol representing natural logarithm of the argument"""
547       def __init__(self,arg):
548           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
549       def __str__(self):
550          return "ln(%s)"%str(self.getArgument(0))
551       def eval(self,argval):
552           return ln(self.getEvaluatedArguments(argval)[0])
553       def _diff(self,arg):
554           return self.getDifferentiatedArguments(arg)[0]/self.getArgument(0)
555    
556  def sin(arg):  def sin(arg):
557      """      """
558      @brief      @brief applies the sin function to arg
559        @param arg (input): argument
     @param arg  
560      """      """
561      if isinstance(arg,escript.Data):      if isinstance(arg,Symbol):
562           return Sin_Symbol(arg)
563        elif hasattr(arg,"sin"):
564         return arg.sin()         return arg.sin()
565      else:      else:
566         return numarray.sin(arg)         return numarray.sin(arg)
567    
568  def tan(arg):  class Sin_Symbol(Symbol):
569       """symbol representing sin of the argument"""
570       def __init__(self,arg):
571           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
572       def __str__(self):
573          return "sin(%s)"%str(self.getArgument(0))
574       def eval(self,argval):
575           return sin(self.getEvaluatedArguments(argval)[0])
576       def _diff(self,arg):
577           return cos(self.getArgument(0))*self.getDifferentiatedArguments(arg)[0]
578    
579    def cos(arg):
580      """      """
581      @brief      @brief applies the cos function to arg
582        @param arg (input): argument
583        """
584        if isinstance(arg,Symbol):
585           return Cos_Symbol(arg)
586        elif hasattr(arg,"cos"):
587           return arg.cos()
588        else:
589           return numarray.cos(arg)
590    
591      @param arg  class Cos_Symbol(Symbol):
592       """symbol representing cos of the argument"""
593       def __init__(self,arg):
594           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
595       def __str__(self):
596          return "cos(%s)"%str(self.getArgument(0))
597       def eval(self,argval):
598           return cos(self.getEvaluatedArguments(argval)[0])
599       def _diff(self,arg):
600           return -sin(self.getArgument(0))*self.getDifferentiatedArguments(arg)[0]
601    
602    def tan(arg):
603      """      """
604      if isinstance(arg,escript.Data):      @brief applies the tan function to arg
605        @param arg (input): argument
606        """
607        if isinstance(arg,Symbol):
608           return Tan_Symbol(arg)
609        elif hasattr(arg,"tan"):
610         return arg.tan()         return arg.tan()
611      else:      else:
612         return numarray.tan(arg)         return numarray.tan(arg)
613    
614  def cos(arg):  class Tan_Symbol(Symbol):
615      """     """symbol representing tan of the argument"""
616      @brief     def __init__(self,arg):
617           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
618       def __str__(self):
619          return "tan(%s)"%str(self.getArgument(0))
620       def eval(self,argval):
621           return tan(self.getEvaluatedArguments(argval)[0])
622       def _diff(self,arg):
623           s=cos(self.getArgument(0))
624           return 1./(s*s)*self.getDifferentiatedArguments(arg)[0]
625    
626      @param arg  def sign(arg):
627      """      """
628      if isinstance(arg,escript.Data):      @brief applies the sign function to arg
629         return arg.cos()      @param arg (input): argument
630        """
631        if isinstance(arg,Symbol):
632           return Sign_Symbol(arg)
633        elif hasattr(arg,"sign"):
634           return arg.sign()
635      else:      else:
636         return numarray.cos(arg)         return numarray.greater(arg,numarray.zeros(arg.shape,numarray.Float))- \
637                  numarray.less(arg,numarray.zeros(arg.shape,numarray.Float))
638    
639    class Sign_Symbol(Symbol):
640       """symbol representing the sign of the argument"""
641       def __init__(self,arg):
642           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
643       def __str__(self):
644          return "sign(%s)"%str(self.getArgument(0))
645       def eval(self,argval):
646           return sign(self.getEvaluatedArguments(argval)[0])
647    
648  def maxval(arg):  def maxval(arg):
649      """      """
650      @brief      @brief returns the maximum value of argument arg""
651        @param arg (input): argument
     @param arg  
652      """      """
653      if isinstance(arg,escript.Data):      if isinstance(arg,Symbol):
654           return Max_Symbol(arg)
655        elif hasattr(arg,"maxval"):
656         return arg.maxval()         return arg.maxval()
657      elif isinstance(arg,float) or isinstance(arg,int):      elif hasattr(arg,"max"):
        return arg  
     else:  
658         return arg.max()         return arg.max()
659        else:
660           return arg
661    
662    class Max_Symbol(Symbol):
663       """symbol representing the maximum value of the argument"""
664       def __init__(self,arg):
665           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
666       def __str__(self):
667          return "maxval(%s)"%str(self.getArgument(0))
668       def eval(self,argval):
669           return maxval(self.getEvaluatedArguments(argval)[0])
670    
671  def minval(arg):  def minval(arg):
672      """      """
673      @brief      @brief returns the minimum value of argument arg""
674        @param arg (input): argument
675        """
676        if isinstance(arg,Symbol):
677           return Min_Symbol(arg)
678        elif hasattr(arg,"maxval"):
679           return arg.minval()
680        elif hasattr(arg,"min"):
681           return arg.min()
682        else:
683           return arg
684    
685    class Min_Symbol(Symbol):
686       """symbol representing the minimum value of the argument"""
687       def __init__(self,arg):
688           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
689       def __str__(self):
690          return "minval(%s)"%str(self.getArgument(0))
691       def eval(self,argval):
692           return minval(self.getEvaluatedArguments(argval)[0])
693    
694    def wherePositive(arg):
695        """
696        @brief returns the positive values of argument arg""
697        @param arg (input): argument
698        """
699        if _testForZero(arg):
700          return 0
701        elif isinstance(arg,Symbol):
702           return WherePositive_Symbol(arg)
703        elif hasattr(arg,"wherePositive"):
704           return arg.minval()
705        elif hasattr(arg,"wherePositive"):
706           numarray.greater(arg,numarray.zeros(arg.shape,numarray.Float))
707        else:
708           if arg>0:
709              return 1.
710           else:
711              return 0.
712    
713    class WherePositive_Symbol(Symbol):
714       """symbol representing the wherePositive function"""
715       def __init__(self,arg):
716           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
717       def __str__(self):
718          return "wherePositive(%s)"%str(self.getArgument(0))
719       def eval(self,argval):
720           return wherePositive(self.getEvaluatedArguments(argval)[0])
721    
722    def whereNegative(arg):
723        """
724        @brief returns the negative values of argument arg""
725        @param arg (input): argument
726        """
727        if _testForZero(arg):
728          return 0
729        elif isinstance(arg,Symbol):
730           return WhereNegative_Symbol(arg)
731        elif hasattr(arg,"whereNegative"):
732           return arg.whereNegative()
733        elif hasattr(arg,"shape"):
734           numarray.less(arg,numarray.zeros(arg.shape,numarray.Float))
735        else:
736           if arg<0:
737              return 1.
738           else:
739              return 0.
740    
741    class WhereNegative_Symbol(Symbol):
742       """symbol representing the whereNegative function"""
743       def __init__(self,arg):
744           Symbol.__init__(self,shape=arg.getShape(),dim=arg.getDim(),args=[arg])
745       def __str__(self):
746          return "whereNegative(%s)"%str(self.getArgument(0))
747       def eval(self,argval):
748           return whereNegative(self.getEvaluatedArguments(argval)[0])
749    
750    def outer(arg0,arg1):
751       if _testForZero(arg0) or _testForZero(arg1):
752          return 0
753       else:
754          if isinstance(arg0,Symbol) or isinstance(arg1,Symbol):
755            return Outer_Symbol(arg0,arg1)
756          elif _identifyShape(arg0)==() or _identifyShape(arg1)==():
757            return arg0*arg1
758          elif isinstance(arg0,numarray.NumArray) and isinstance(arg1,numarray.NumArray):
759            return numarray.outer(arg0,arg1)
760          else:
761            if arg0.getRank()==1 and arg1.getRank()==1:
762              out=escript.Data(0,(arg0.getShape()[0],arg1.getShape()[0]),arg1.getFunctionSpace())
763              for i in range(arg0.getShape()[0]):
764                for j in range(arg1.getShape()[0]):
765                    out[i,j]=arg0[i]*arg1[j]
766              return out
767            else:
768              raise ValueError,"outer is not fully implemented yet."
769    
770    class Outer_Symbol(Symbol):
771       """symbol representing the outer product of its two arguments"""
772       def __init__(self,arg0,arg1):
773           a=[arg0,arg1]
774           s=tuple(list(_identifyShape(arg0))+list(_identifyShape(arg1)))
775           Symbol.__init__(self,shape=s,dim=_extractDim(a),args=a)
776       def __str__(self):
777          return "outer(%s,%s)"%(str(self.getArgument(0)),str(self.getArgument(1)))
778       def eval(self,argval):
779           a=self.getEvaluatedArguments(argval)
780           return outer(a[0],a[1])
781       def _diff(self,arg):
782           a=self.getDifferentiatedArguments(arg)
783           return outer(a[0],self.getArgument(1))+outer(self.getArgument(0),a[1])
784    
785    def interpolate(arg,where):
786        """
787        @brief interpolates the function into the FunctionSpace where.
788    
789        @param arg    interpolant
790        @param where  FunctionSpace to interpolate to
791        """
792        if _testForZero(arg):
793          return 0
794        elif isinstance(arg,Symbol):
795           return Interpolated_Symbol(arg,where)
796        else:
797           return escript.Data(arg,where)
798    
799    def Interpolated_Symbol(Symbol):
800       """symbol representing the integral of the argument"""
801       def __init__(self,arg,where):
802            Symbol.__init__(self,shape=_extractShape(arg),dim=_extractDim([arg]),args=[arg,where])
803       def __str__(self):
804          return "interpolated(%s)"%(str(self.getArgument(0)))
805       def eval(self,argval):
806           a=self.getEvaluatedArguments(argval)
807           return integrate(a[0],where=self.getArgument(1))
808       def _diff(self,arg):
809           a=self.getDifferentiatedArguments(arg)
810           return integrate(a[0],where=self.getArgument(1))
811    
812    def grad(arg,where=None):
813        """
814        @brief returns the spatial gradient of arg at where.
815    
816        @param arg:   Data object representing the function which gradient to be calculated.
817        @param where: FunctionSpace in which the gradient will be calculated. If not present or
818                      None an appropriate default is used.
819        """
820        if _testForZero(arg):
821          return 0
822        elif isinstance(arg,Symbol):
823           return Grad_Symbol(arg,where)
824        elif hasattr(arg,"grad"):
825           if where==None:
826              return arg.grad()
827           else:
828              return arg.grad(where)
829        else:
830           return arg*0.
831    
832    def Grad_Symbol(Symbol):
833       """symbol representing the gradient of the argument"""
834       def __init__(self,arg,where=None):
835           d=_extractDim([arg])
836           s=tuple(list(_identifyShape([arg])).append(d))
837           Symbol.__init__(self,shape=s,dim=_extractDim([arg]),args=[arg,where])
838       def __str__(self):
839          return "grad(%s)"%(str(self.getArgument(0)))
840       def eval(self,argval):
841           a=self.getEvaluatedArguments(argval)
842           return grad(a[0],where=self.getArgument(1))
843       def _diff(self,arg):
844           a=self.getDifferentiatedArguments(arg)
845           return grad(a[0],where=self.getArgument(1))
846    
847    def integrate(arg,where=None):
848        """
849        @brief return the integral if the function represented by Data object arg over its domain.
850    
851        @param arg:   Data object representing the function which is integrated.
852        @param where: FunctionSpace in which the integral is calculated. If not present or
853                      None an appropriate default is used.
854        """
855        if _testForZero(arg):
856          return 0
857        elif isinstance(arg,Symbol):
858           return Integral_Symbol(arg,where)
859        else:    
860           if not where==None: arg=escript.Data(arg,where)
861           if arg.getRank()==0:
862             return arg.integrate()[0]
863           else:
864             return arg.integrate()
865    
866    def Integral_Symbol(Float_Symbol):
867       """symbol representing the integral of the argument"""
868       def __init__(self,arg,where=None):
869           Float_Symbol.__init__(self,shape=_identifyShape([arg]),args=[arg,where])
870       def __str__(self):
871          return "integral(%s)"%(str(self.getArgument(0)))
872       def eval(self,argval):
873           a=self.getEvaluatedArguments(argval)
874           return integrate(a[0],where=self.getArgument(1))
875       def _diff(self,arg):
876           a=self.getDifferentiatedArguments(arg)
877           return integrate(a[0],where=self.getArgument(1))
878    
879    #=============================
880    #
881    # wrapper for various functions: if the argument has attribute the function name
882    # as an argument it calls the corresponding methods. Otherwise the corresponding
883    # numarray function is called.
884    
885    # functions involving the underlying Domain:
886    
887    
888    # functions returning Data objects:
889    
890    def transpose(arg,axis=None):
891        """
892        @brief returns the transpose of the Data object arg.
893    
894      @param arg      @param arg
895      """      """
896        if axis==None:
897           r=0
898           if hasattr(arg,"getRank"): r=arg.getRank()
899           if hasattr(arg,"rank"): r=arg.rank
900           axis=r/2
901        if isinstance(arg,Symbol):
902           return Transpose_Symbol(arg,axis=r)
903      if isinstance(arg,escript.Data):      if isinstance(arg,escript.Data):
904         return arg.minval()         # hack for transpose
905      elif isinstance(arg,float) or isinstance(arg,int):         r=arg.getRank()
906         return arg         if r!=2: raise ValueError,"Tranpose only avalaible for rank 2 objects"
907           s=arg.getShape()
908           out=escript.Data(0.,(s[1],s[0]),arg.getFunctionSpace())
909           for i in range(s[0]):
910              for j in range(s[1]):
911                 out[j,i]=arg[i,j]
912           return out
913           # end hack for transpose
914           return arg.transpose(axis)
915      else:      else:
916         return arg.min()         return numarray.transpose(arg,axis=axis)
917    
918    def trace(arg,axis0=0,axis1=1):
919        """
920        @brief return
921    
922        @param arg
923        """
924        if isinstance(arg,Symbol):
925           s=list(arg.getShape())        
926           s=tuple(s[0:axis0]+s[axis0+1:axis1]+s[axis1+1:])
927           return Trace_Symbol(arg,axis0=axis0,axis1=axis1)
928        elif isinstance(arg,escript.Data):
929           # hack for trace
930           s=arg.getShape()
931           if s[axis0]!=s[axis1]:
932               raise ValueError,"illegal axis in trace"
933           out=escript.Scalar(0.,arg.getFunctionSpace())
934           for i in range(s[0]):
935              for j in range(s[1]):
936                 out+=arg[i,j]
937           return out
938           # end hack for trace
939           return arg.transpose(axis0=axis0,axis1=axis1)
940        else:
941           return numarray.trace(arg,axis0=axis0,axis1=axis1)
942    
943    def Trace_Symbol(Symbol):
944        pass
945    
946  def length(arg):  def length(arg):
947      """      """
# Line 263  def length(arg): Line 980  def length(arg):
980                        sum+=arg[i,j,k,l]**2                        sum+=arg[i,j,k,l]**2
981            return sqrt(sum)            return sqrt(sum)
982         else:         else:
983            raise SystemError,"length is not been implemented yet"            raise SystemError,"length is not been fully implemented yet"
984         # return arg.length()            # return arg.length()
985      else:      else:
986         return sqrt((arg**2).sum())         return sqrt((arg**2).sum())
987    
# Line 272  def deviator(arg): Line 989  def deviator(arg):
989      """      """
990      @brief      @brief
991    
992      @param arg1      @param arg0
993      """      """
994      if isinstance(arg,escript.Data):      if isinstance(arg,escript.Data):
995          shape=arg.getShape()          shape=arg.getShape()
# Line 284  def deviator(arg): Line 1001  def deviator(arg):
1001            raise ValueError,"Deviator requires a square matrix"            raise ValueError,"Deviator requires a square matrix"
1002      return arg-1./(shape[0]*1.)*trace(arg)*kronecker(shape[0])      return arg-1./(shape[0]*1.)*trace(arg)*kronecker(shape[0])
1003    
1004  def inner(arg1,arg2):  def inner(arg0,arg1):
1005      """      """
1006      @brief      @brief
1007    
1008      @param arg1, arg2      @param arg0, arg1
1009      """      """
1010      sum=escript.Scalar(0,arg1.getFunctionSpace())      sum=escript.Scalar(0,arg0.getFunctionSpace())
1011      if arg.getRank()==0:      if arg.getRank()==0:
1012            return arg1*arg2            return arg0*arg1
1013      elif arg.getRank()==1:      elif arg.getRank()==1:
1014           sum=escript.Scalar(0,arg.getFunctionSpace())           sum=escript.Scalar(0,arg.getFunctionSpace())
1015           for i in range(arg.getShape()[0]):           for i in range(arg.getShape()[0]):
1016              sum+=arg1[i]*arg2[i]              sum+=arg0[i]*arg1[i]
1017      elif arg.getRank()==2:      elif arg.getRank()==2:
1018          sum=escript.Scalar(0,arg.getFunctionSpace())          sum=escript.Scalar(0,arg.getFunctionSpace())
1019          for i in range(arg.getShape()[0]):          for i in range(arg.getShape()[0]):
1020             for j in range(arg.getShape()[1]):             for j in range(arg.getShape()[1]):
1021                sum+=arg1[i,j]*arg2[i,j]                sum+=arg0[i,j]*arg1[i,j]
1022      elif arg.getRank()==3:      elif arg.getRank()==3:
1023          sum=escript.Scalar(0,arg.getFunctionSpace())          sum=escript.Scalar(0,arg.getFunctionSpace())
1024          for i in range(arg.getShape()[0]):          for i in range(arg.getShape()[0]):
1025              for j in range(arg.getShape()[1]):              for j in range(arg.getShape()[1]):
1026                 for k in range(arg.getShape()[2]):                 for k in range(arg.getShape()[2]):
1027                    sum+=arg1[i,j,k]*arg2[i,j,k]                    sum+=arg0[i,j,k]*arg1[i,j,k]
1028      elif arg.getRank()==4:      elif arg.getRank()==4:
1029          sum=escript.Scalar(0,arg.getFunctionSpace())          sum=escript.Scalar(0,arg.getFunctionSpace())
1030          for i in range(arg.getShape()[0]):          for i in range(arg.getShape()[0]):
1031             for j in range(arg.getShape()[1]):             for j in range(arg.getShape()[1]):
1032                for k in range(arg.getShape()[2]):                for k in range(arg.getShape()[2]):
1033                   for l in range(arg.getShape()[3]):                   for l in range(arg.getShape()[3]):
1034                      sum+=arg1[i,j,k,l]*arg2[i,j,k,l]                      sum+=arg0[i,j,k,l]*arg1[i,j,k,l]
1035      else:      else:
1036            raise SystemError,"inner is not been implemented yet"            raise SystemError,"inner is not been implemented yet"
1037      return sum      return sum
1038    
1039  def sign(arg):  def matrixmult(arg0,arg1):
     """  
     @brief  
1040    
1041      @param arg      if isinstance(arg1,numarray.NumArray) and isinstance(arg0,numarray.NumArray):
1042      """          numarray.matrixmult(arg0,arg1)
     if isinstance(arg,escript.Data):  
        return arg.sign()  
1043      else:      else:
1044         return numarray.greater(arg,numarray.zeros(arg.shape))-numarray.less(arg,numarray.zeros(arg.shape))        # escript.matmult(arg0,arg1)
1045          if isinstance(arg1,escript.Data) and not isinstance(arg0,escript.Data):
1046            arg0=escript.Data(arg0,arg1.getFunctionSpace())
1047          elif isinstance(arg0,escript.Data) and not isinstance(arg1,escript.Data):
1048            arg1=escript.Data(arg1,arg0.getFunctionSpace())
1049          if arg0.getRank()==2 and arg1.getRank()==1:
1050              out=escript.Data(0,(arg0.getShape()[0],),arg0.getFunctionSpace())
1051              for i in range(arg0.getShape()[0]):
1052                 for j in range(arg0.getShape()[1]):
1053                   # uses Data object slicing, plus Data * and += operators
1054                   out[i]+=arg0[i,j]*arg1[j]
1055              return out
1056          else:
1057              raise SystemError,"matrixmult is not fully implemented yet!"
1058    
1059    #=========================================================
1060  # reduction operations:  # reduction operations:
1061    #=========================================================
1062  def sum(arg):  def sum(arg):
1063      """      """
1064      @brief      @brief
# Line 392  def Lsup(arg): Line 1119  def Lsup(arg):
1119      else:      else:
1120         return max(numarray.abs(arg))         return max(numarray.abs(arg))
1121    
1122  def Linf(arg):  def dot(arg0,arg1):
1123      """      """
1124      @brief      @brief
1125    
1126      @param arg      @param arg
1127      """      """
1128      if isinstance(arg,escript.Data):      if isinstance(arg0,escript.Data):
1129         return arg.Linf()         return arg0.dot(arg1)
     elif isinstance(arg,float) or isinstance(arg,int):  
        return abs(arg)  
     else:  
        return min(numarray.abs(arg))  
   
 def dot(arg1,arg2):  
     """  
     @brief  
   
     @param arg  
     """  
     if isinstance(arg1,escript.Data):  
        return arg1.dot(arg2)  
1130      elif isinstance(arg1,escript.Data):      elif isinstance(arg1,escript.Data):
1131         return arg2.dot(arg1)         return arg1.dot(arg0)
1132      else:      else:
1133         return numarray.dot(arg1,arg2)         return numarray.dot(arg0,arg1)
1134    
1135  def kronecker(d):  def kronecker(d):
1136     return numarray.identity(d)     if hasattr(d,"getDim"):
1137          return numarray.identity(d.getDim())
1138       else:
1139          return numarray.identity(d)
1140    
1141  def unit(i,d):  def unit(i,d):
1142     """     """
# Line 427  def unit(i,d): Line 1144  def unit(i,d):
1144     @param d dimension     @param d dimension
1145     @param i index     @param i index
1146     """     """
1147     e = numarray.zeros((d,))     e = numarray.zeros((d,),numarray.Float)
1148     e[i] = 1.0     e[i] = 1.0
1149     return e     return e
1150    
1151    # ============================================
1152    #   testing
1153    # ============================================
1154    
1155    if __name__=="__main__":
1156      u=ScalarSymbol(dim=2,name="u")
1157      v=ScalarSymbol(dim=2,name="v")
1158      v=VectorSymbol(2,"v")
1159      u=VectorSymbol(2,"u")
1160    
1161      print u+5,(u+5).diff(u)
1162      print 5+u,(5+u).diff(u)
1163      print u+v,(u+v).diff(u)
1164      print v+u,(v+u).diff(u)
1165    
1166      print u*5,(u*5).diff(u)
1167      print 5*u,(5*u).diff(u)
1168      print u*v,(u*v).diff(u)
1169      print v*u,(v*u).diff(u)
1170    
1171      print u-5,(u-5).diff(u)
1172      print 5-u,(5-u).diff(u)
1173      print u-v,(u-v).diff(u)
1174      print v-u,(v-u).diff(u)
1175    
1176      print u/5,(u/5).diff(u)
1177      print 5/u,(5/u).diff(u)
1178      print u/v,(u/v).diff(u)
1179      print v/u,(v/u).diff(u)
1180    
1181      print u**5,(u**5).diff(u)
1182      print 5**u,(5**u).diff(u)
1183      print u**v,(u**v).diff(u)
1184      print v**u,(v**u).diff(u)
1185    
1186      print exp(u),exp(u).diff(u)
1187      print sqrt(u),sqrt(u).diff(u)
1188      print log(u),log(u).diff(u)
1189      print sin(u),sin(u).diff(u)
1190      print cos(u),cos(u).diff(u)
1191      print tan(u),tan(u).diff(u)
1192      print sign(u),sign(u).diff(u)
1193      print abs(u),abs(u).diff(u)
1194      print wherePositive(u),wherePositive(u).diff(u)
1195      print whereNegative(u),whereNegative(u).diff(u)
1196      print maxval(u),maxval(u).diff(u)
1197      print minval(u),minval(u).diff(u)
1198    
1199      g=grad(u)
1200      print diff(5*g,g)
1201      4*(g+transpose(g))/2+6*trace(g)*kronecker(3)
1202    
1203    #
1204    # $Log$
1205    # Revision 1.13  2005/07/22 03:53:01  jgs
1206    # Merge of development branch back to main trunk on 2005-07-22
1207    #
1208    # Revision 1.12  2005/07/20 06:14:58  jgs
1209    # added ln(data) style wrapper for data.ln() - also added corresponding
1210    # implementation of Ln_Symbol class (not sure if this is right though)
1211    #
1212    # Revision 1.11  2005/07/08 04:07:35  jgs
1213    # Merge of development branch back to main trunk on 2005-07-08
1214    #
1215    # Revision 1.10  2005/06/09 05:37:59  jgs
1216    # Merge of development branch back to main trunk on 2005-06-09
1217    #
1218    # Revision 1.2.2.19  2005/07/21 04:01:28  jgs
1219    # minor comment fixes
1220    #
1221    # Revision 1.2.2.18  2005/07/21 01:02:43  jgs
1222    # commit ln() updates to development branch version
1223    #
1224    # Revision 1.12  2005/07/20 06:14:58  jgs
1225    # added ln(data) style wrapper for data.ln() - also added corresponding
1226    # implementation of Ln_Symbol class (not sure if this is right though)
1227    #
1228    # Revision 1.11  2005/07/08 04:07:35  jgs
1229    # Merge of development branch back to main trunk on 2005-07-08
1230    #
1231    # Revision 1.10  2005/06/09 05:37:59  jgs
1232    # Merge of development branch back to main trunk on 2005-06-09
1233    #
1234    # Revision 1.2.2.17  2005/07/07 07:28:58  gross
1235    # some stuff added to util.py to improve functionality
1236    #
1237    # Revision 1.2.2.16  2005/06/30 01:53:55  gross
1238    # a bug in coloring fixed
1239    #
1240    # Revision 1.2.2.15  2005/06/29 02:36:43  gross
1241    # Symbols have been introduced and some function clarified. needs much more work
1242    #
1243    # Revision 1.2.2.14  2005/05/20 04:05:23  gross
1244    # some work on a darcy flow started
1245    #
1246    # Revision 1.2.2.13  2005/03/16 05:17:58  matt
1247    # Implemented unit(idx, dim) to create cartesian unit basis vectors to
1248    # complement kronecker(dim) function.
1249    #
1250    # Revision 1.2.2.12  2005/03/10 08:14:37  matt
1251    # Added non-member Linf utility function to complement Data::Linf().
1252    #
1253    # Revision 1.2.2.11  2005/02/17 05:53:25  gross
1254    # some bug in saveDX fixed: in fact the bug was in
1255    # DataC/getDataPointShape
1256    #
1257    # Revision 1.2.2.10  2005/01/11 04:59:36  gross
1258    # automatic interpolation in integrate switched off
1259    #
1260    # Revision 1.2.2.9  2005/01/11 03:38:13  gross
1261    # Bug in Data.integrate() fixed for the case of rank 0. The problem is not totallly resolved as the method should return a scalar rather than a numarray object in the case of rank 0. This problem is fixed by the util.integrate wrapper.
1262    #
1263    # Revision 1.2.2.8  2005/01/05 04:21:41  gross
1264    # FunctionSpace checking/matchig in slicing added
1265    #
1266    # Revision 1.2.2.7  2004/12/29 05:29:59  gross
1267    # AdvectivePDE successfully tested for Peclet number 1000000. there is still a problem with setValue and Data()
1268    #
1269    # Revision 1.2.2.6  2004/12/24 06:05:41  gross
1270    # some changes in linearPDEs to add AdevectivePDE
1271    #
1272    # Revision 1.2.2.5  2004/12/17 00:06:53  gross
1273    # mk sets ESYS_ROOT is undefined
1274    #
1275    # Revision 1.2.2.4  2004/12/07 03:19:51  gross
1276    # options for GMRES and PRES20 added
1277    #
1278    # Revision 1.2.2.3  2004/12/06 04:55:18  gross
1279    # function wraper extended
1280    #
1281    # Revision 1.2.2.2  2004/11/22 05:44:07  gross
1282    # a few more unitary functions have been added but not implemented in Data yet
1283    #
1284    # Revision 1.2.2.1  2004/11/12 06:58:15  gross
1285    # a lot of changes to get the linearPDE class running: most important change is that there is no matrix format exposed to the user anymore. the format is chosen by the Domain according to the solver and symmetry
1286    #
1287    # Revision 1.2  2004/10/27 00:23:36  jgs
1288    # fixed minor syntax error
1289    #
1290    # Revision 1.1.1.1  2004/10/26 06:53:56  jgs
1291    # initial import of project esys2
1292    #
1293    # Revision 1.1.2.3  2004/10/26 06:43:48  jgs
1294    # committing Lutz's and Paul's changes to brach jgs
1295    #
1296    # Revision 1.1.4.1  2004/10/20 05:32:51  cochrane
1297    # Added incomplete Doxygen comments to files, or merely put the docstrings that already exist into Doxygen form.
1298    #
1299    # Revision 1.1  2004/08/05 03:58:27  gross
1300    # Bug in Assemble_NodeCoordinates fixed
1301    #
1302    #

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